Application of Cuckoo Search Algorithm for Image Segmentation
Image analysis has a large interest in remote sensing, it is used for extract pertinent information, and the segmentation is found at the bottom of each analysis. Image segmentation is also considered as one of the most difficult, critical and essential tasks in image processing. It determines the quality of the final analysis result. Image segmentation can be viewed as an optimization problem, Meta heuristic optimization methods and in particular bio-inspired methods are very used in image segmentation, they can be applied to any mono or multiobjective optimization problem. In this paper we present a meta heuristic approach based on Cuckoo Search Algorithm (CSA) for the purpose of solving the problem of image segmentation in general and in particularly the satellite images segmentation.
Copyright © 2017 Praise Worthy Prize - All rights reserved.
Abdul Khalid NE, Ariff N Md, Yahya S, and Noor NM: A Review of Bio-inspired Algorithms as Image Processing Techniques, In proceeding of: Software Engineering and Computer Systems - Second International Conference, ICSECS 2011, Kuantan, Pahang, Malaysia, June 27-29. (2011)
Yang X-S: Nature-Inspired Metaheuristic Algorithms, Second Edition, Luniver Press (2010).
Dariusz K and Heitor SL: Nature-inspired collective intelligence in theory and practice, Editorial, Information Sciences 182 (2012).
Haralick RM and Shapiro LG: Image Segmentation Techniques. Computer Vision, Graphics, and Image Processing 29(1): 100-132 (1985).
Bong C and Rajeswari M: Multi-objective nature-inspired clustering and classification techniques for image segmentation, Applied Soft Computing 11, 3271–3282 (2011).
Rajeshwar D, Priyanka and Swapna D: Image Segmentation Techniques, IJECT Vol. 3, Issue 1, Jan. - March (2012).
Swagatam D and Amit K: Automatic image pixel clustering with an improved differential evolution, Applied Soft Computing 9 (2009).
Jain AK ,Murty MN and Flynn PJ: Data clustering: a review, ACM Computing Surveys 31 (3) (1999).
Bensaid AM, Hall LO, Bezdek JC, Clarke LP, Silbiger ML, Arrington JA and Murtagh RF: Validity-guided (Re) Clustering with applications to image segmentation, IEEE Transactions on Fuzzy Systems, 4:112-123, (1996).
Chin-Wei.B et Rajeswari. M: Multiobjective Optimization Approaches in Image Segmentation – The Directions and Challenges, Int. J. Advance. Soft Comput. Appl., Vol. 2, No. 1. ( 2010)
Jose Alfredo F Costa and Jackson G de Souza: Image Segmentation through Clustering Based on Natural Computing Techniques, In: Image Segmentation, Pei-Gee Ho (Ed.), pp. 57-82, ISBN: 978-953-307-228-9, InTech. Austria, (2011).
Mahi, H. and H.F. Izabatene,. Segmentation of satellite imagery using RBF neural network and genetic algorithm. Asian J. Applied Sci., 4: 186-194.
Moravej, Z., Akhlaghi, A., A new approach for DG allocation in distribution network with time variable loads using cuckoo search, (2012) International Review of Electrical Engineering (IREE), 7 (2), pp. 4027-4034.
Thomas, J., Kulanthaivel, G., Preterm birth prediction using cuckoo search-based fuzzy min-max neural network, (2013) International Review on Computers and Software (IRECOS), 8 (8), pp. 1854-1862.
Velayudham, A., Kanthavel, R., Kumar, K., A Novel and Hybrid Optimization Mechanism For Denoising And Classification Of Medical Images using DTCWPT And Neuro-Fuzzy Classifiers, (2014) International Review on Computers and Software (IRECOS), 9 (3), pp. 513-525.
Manikandan, P., Selvarajan, S., A hybrid optimization algorithm based on cuckoo search and PSO for data clustering, (2013) International Review on Computers and Software (IRECOS), 8 (9), pp. 2278-2287.
George, G., Parthiban, L., FCM-FCS: Hybridization of Fractional Cuckoo Search with FCM for High Dimensional Data Clustering Process, (2013) International Review on Computers and Software (IRECOS), 8 (11), pp. 2576-2585.
Shair, E., Khor, S., Abdullah, A., Jaafar, H., Mohd Ali, N., Zainal Abidin, A., A Brief Review of Cuckoo Search Algorithm (CSA) Research Progression from 2010 to 2013, (2014) International Review of Automatic Control (IREACO), 7 (5), pp. 428-435.
Yang, X-S. and Deb, S. 2014. Cuckoo search: recent advances and applications. Neural Comput and Application 24 (1): 69–174.
Azizah, B. M., Azlan, M.Z. and Nor, E.N.B. 2014. Cuckoo Search Algorithm for Optimization Problems—A Literature Review and its Applications. Applied Artificial Intelligence: An International Journal, 28 (5): 419-448.
Yang, X-S. and Deb, S. Cuckoo search: recent advances and applications. Neural Comput and Application 24 (1), 69–174. (2014).
Payne RB, Sorenson MD and Klitz K: The Cuckoos, Oxford University Press, New York, (2005).
Yang X-S and Deb S: Cuckoo search via Lévy flights, In: Proceedings of World Congress on Nature & Biologically Inspired Computing. IEEE Publications, USA, pp 210–214 (2009).
Gandomi, A.H., Yang, X-S. & Alavi A.H.. Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Engineering with Computers, 29 (1), 17-35 (2013).
Xie.X. L and Beni.G: A validity measure for fuzzy clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, pp.841–847, (1991) .
Zexuan J, Yong X, Qiang C, Quansen S, Deshen X and David DF: Fuzzy c-means clustering with weighted image patch for image segmentation, Applied Soft Computing 12, 1659–1667, (2012).
Davies DL and Bouldin DW: A cluster separation measure, IEEE Trans. Pattern Anal, Mach. Intelligence, 1, 224–227, (1979).
Demidova, L., Sokolova, Y., Nikulchev, E., Use of Fuzzy Clustering Algorithms Ensemble for SVM Classifier Development, (2015) International Review on Modelling and Simulations (IREMOS), 8 (4), pp. 446-457.
Del Pizzo, A., Meo, S., Brando, G., Dannier, A., Ciancetta, F., An Energy Management Strategy for Fuel-cell Hybrid Electric Vehicles via Particle Swarm Optimization Approach, (2014) International Review on Modelling and Simulations (IREMOS), 7 (4), pp. 543-553.
Saraereh, O., Al Saraira, A., Alsafasfeh, Q., Arfoa, A., Bio-Inspired Algorithms Applied on Microstrip Patch Antennas: a Review, (2016) International Journal on Communications Antenna and Propagation (IRECAP), 6 (6), pp. 336-347.
El-Arini, M., Othman, A., Othman, A., Said, T., Said, T., Particle Swarm Optimization and Genetic Algorithm for Convex and Non-convex Economic Dispatch, (2014) International Review of Electrical Engineering (IREE), 9 (1), pp. 127-135.
- There are currently no refbacks.
Please send any questions about this web site to email@example.com
Copyright © 2005-2018 Praise Worthy Prize